Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs.

Cerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. Thanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.

group is at the heart of Cerebras' mission to deliver the world’s fastest AI inference. Our team builds the foundational software and hardware infrastructure that powers low-latency, high-speed, high-throughput deployment on the Cerebras Wafer-Scale Engine (WSE). team plays a pivotal role in shaping the performance and scalability of AI inference on one of the most advanced computing systems ever built. We drive the bring-up of core inference capabilities and deliver performance improvements at every stage of development – from early prototyping to production deployment.

We're looking for passionate engineers to join us in redefining the limits of AI inference. If you thrive on building systems that measure, analyze, and optimize performance at scale, this is your prospect to make a transformative impact on the future of AI.





Design and implement end-to-end telemetry systems across the software stack, providing deep visibility into inference performance and enabling rapid iteration before and after deployment.

Architect, build, and scale the automation that generates, analyzes, and visualizes performance data used to inform business decisions across engineering and leadership.

Performance Analysis – Dive deep into system behavior, dissect performance bottlenecks, and deliver actionable insights that directly influence which features ship and how they evolve.

Partner closely with Core Platform teams to define rigorous testing methodologies that validate inference features for peak performance.

Bachelor’s or Master’s degree in Computer Engineering, Systems Engineering, or a related field.

Proficiency in Python and/or C++ programming.

Proven experience in building and scaling automated infrastructure.

Strong background in throughput and performance optimization techniques, especially in complex, large-scale systems.

Familiarity with problem-solving at the intersection of hardware and software.

Hands-on experience with AI workloads and architectures is a plus.

On-site or hybrid at our Toronto office

People who are serious about software make their own hardware. At Cerebras we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. Build a breakthrough AI platform beyond the constraints of the GPU.

Publish and open source their cutting-edge AI research.

Work on one of the fastest AI supercomputers in the world.

Our simple, non-corporate work culture that respects individual beliefs.

Apply today and become part of the forefront of groundbreaking advancements in AI! We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.

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📌 Machine Learning Performance Architecture Engineer (Toronto)
🏢 Cerebras
📍 Toronto